Chapter 5 Community composition
5.1 Filter data
Filter samples with high host data
sample_metadata <- sample_metadata %>%
filter(!sample %in% c("EHI02721", "EHI02712", "EHI02700", "EHI02720", "EHI02749", "EHI02719", "EHI02729", "EHI02715", "EHI02722"))
genome_counts_filt <- genome_counts %>%
select(one_of(c("genome",sample_metadata$sample)))%>%
filter(rowSums(. != 0, na.rm = TRUE) > 0) %>%
select_if(~!all(. == 0))
genome_counts <- genome_counts_filt
genome_metadata <- genome_metadata %>%
semi_join(., genome_counts_filt, by = "genome") %>%
arrange(match(genome,genome_counts_filt$genome))
genome_tree <- keep.tip(genome_tree, tip=genome_metadata$genome) # keep only MAG tips
#load("data/genome_gifts.Rdata")Make a phyloseq object
phylo_samples <- sample_metadata %>%
column_to_rownames("sample") %>%
sample_data() #convert to phyloseq sample_data object
phylo_genome <- genome_counts_filt %>%
column_to_rownames("genome") %>%
otu_table(., taxa_are_rows = TRUE)
phylo_taxonomy <- genome_metadata %>%
column_to_rownames("genome") %>%
as.matrix() %>%
tax_table() #convert to phyloseq tax_table object
phylo_tree <- phy_tree(genome_tree)
physeq_genome <- phyloseq(phylo_genome, phylo_taxonomy, phylo_samples,phylo_tree)
physeq_genome_clr <- microbiome::transform(physeq_genome, 'clr')5.3 Taxonomy overview
5.3.1 Stacked barplot
genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS normalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>% #reduce to minimum number of columns
left_join(., genome_metadata, by = join_by(genome == genome)) %>% #append genome metadata
left_join(., sample_metadata, by = join_by(sample == sample)) %>% #append sample metadata
filter(diet!="Post_grass") %>%
filter(count > 0) %>% #filter 0 counts
ggplot(., aes(x=sample,y=count, fill=phylum, group=phylum)) + #grouping enables keeping the same sorting of taxonomic units
geom_bar(stat="identity", colour="white", linewidth=0.1) + #plot stacked bars with white borders
scale_fill_manual(values=phylum_colors) +
facet_grid(~factor(diet, labels=c("Pre_grass" = "Captive-born","Wild" = "Wild-born")), scale="free", space = "free")+
# facet_nested(. ~ region+diet, scales="free") + #facet per day and treatment
guides(fill = guide_legend(ncol = 1)) +
theme(
axis.title.x = element_blank(),
panel.background = element_blank(),
panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
strip.background = element_rect(fill = "white"),
strip.text = element_text(size = 12, lineheight = 0.6),
strip.placement = "outside",
axis.text.x = element_blank(), axis.ticks.x = element_blank(),
axis.line = element_line(linewidth = 0.5, linetype = "solid", colour = "black")) +
labs(fill="Phylum",y = "Relative abundance",x="Samples")Number of bacteria phyla
[1] 14
Bacteria phyla in wild individuals
[1] 14
Bacteria phyla captive animals
[1] 14
Bacteria phyla before grass is included in the diet
[1] 14
Bacteria phyla after grass is included in the diet
[1] 14
Number of Archaea phyla
[1] 1
Archaea phyla in wild individuals
[1] 0
Archaea phyla before grass is included in the diet
[1] "p__Methanobacteriota"
Archaea phyla after grass is included in the diet
[1] "p__Methanobacteriota"
5.3.2 Genus and species annotation
Number of MAGs without species-level annotation
# A tibble: 1 × 1
Mag_nospecies
<int>
1 749
# A tibble: 14 × 4
phylum count_nospecies count_total percentage
<chr> <int> <int> <dbl>
1 p__Actinomycetota 15 15 100
2 p__Bacillota 52 53 98.1
3 p__Bacillota_A 516 526 98.1
4 p__Bacillota_B 2 2 100
5 p__Bacillota_C 6 9 66.7
6 p__Bacteroidota 43 127 33.9
7 p__Campylobacterota 1 1 100
8 p__Cyanobacteriota 6 7 85.7
9 p__Desulfobacterota 12 12 100
10 p__Patescibacteria 13 13 100
11 p__Pseudomonadota 32 39 82.1
12 p__Spirochaetota 2 2 100
13 p__Synergistota 18 18 100
14 p__Verrucomicrobiota 31 35 88.6
Percentage of MAGs without species-level annotation
Mag_nospecies
1 87.09302
Number of MAGs without genera-level annotation
79
5.3.3 Phylum relative abundances
phylum_summary <- genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS nornalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>%
left_join(sample_metadata, by = join_by(sample == sample)) %>%
left_join(genome_metadata, by = join_by(genome == genome)) %>%
group_by(sample,phylum,region, diet) %>%
summarise(relabun=sum(count))phylum_arrange <- phylum_summary %>%
group_by(phylum) %>%
summarise(mean=mean(relabun)) %>%
arrange(-mean) %>%
select(phylum) %>%
pull()
phylum_summary %>%
filter(phylum %in% phylum_arrange) %>%
mutate(phylum=factor(phylum,levels=rev(phylum_arrange))) %>%
ggplot(aes(x=relabun, y=phylum, group=phylum, color=phylum)) +
scale_color_manual(values=phylum_colors[rev(phylum_arrange)]) +
geom_jitter(alpha=0.5) +
theme_minimal() +
theme(legend.position="none") +
labs(y="Phylum",x="Relative abundance")5.3.3.1 Origin: Wild vs Captive
phylum_summary %>%
group_by(phylum) %>%
summarise(total_mean=mean(relabun*100, na.rm=T),
total_sd=sd(relabun*100, na.rm=T),
Wild_mean=mean(relabun[diet=="Wild"]*100, na.rm=T),
Wild_sd=sd(relabun[diet=="Wild"]*100, na.rm=T),
Captive_mean=mean(relabun[diet=="Pre_grass"]*100, na.rm=T),
Captive_sd=sd(relabun[diet=="Pre_grass"]*100, na.rm=T)) %>%
mutate(total=str_c(round(total_mean,3),"±",round(total_sd,3)),
Wild=str_c(round(Wild_mean,3),"±",round(Wild_sd,3)),
Captive=str_c(round(Captive_mean,3),"±",round(Captive_sd,3))) %>%
arrange(-total_mean) %>%
dplyr::select(phylum,total,Wild,Captive)# A tibble: 15 × 4
phylum total Wild Captive
<chr> <chr> <chr> <chr>
1 p__Bacillota_A 57.243±12.618 48.636±13.52 59.846±10.725
2 p__Bacteroidota 25.787±10.113 26.889±11.805 24.986±10.083
3 p__Bacillota 4.118±7.202 5.066±11.152 4.949±5.297
4 p__Spirochaetota 3.911±10.011 11.731±14.792 0.001±0.001
5 p__Verrucomicrobiota 2.264±5.722 1.472±0.715 1.449±1.295
6 p__Pseudomonadota 1.626±3.328 0.511±0.397 3.082±5.382
7 p__Patescibacteria 0.987±1.542 0.212±0.253 2.177±2.223
8 p__Synergistota 0.96±0.852 1.865±0.83 0.45±0.39
9 p__Bacillota_C 0.844±0.795 1.696±0.674 0.386±0.36
10 p__Actinomycetota 0.78±0.985 0.427±0.459 1.217±1.147
11 p__Cyanobacteriota 0.708±2.081 0.277±0.614 0.916±3.024
12 p__Desulfobacterota 0.586±0.396 0.991±0.315 0.41±0.256
13 p__Bacillota_B 0.104±0.145 0.228±0.203 0.042±0.024
14 p__Methanobacteriota 0.082±0.217 0±0 0.09±0.228
15 p__Campylobacterota 0±0 0±0 0±0
5.3.3.2 Origin and diet
phylum_summary %>%
group_by(phylum) %>%
summarise(total_mean=mean(relabun*100, na.rm=T),
total_sd=sd(relabun*100, na.rm=T),
Wild_mean=mean(relabun[diet=="Wild"]*100, na.rm=T),
Wild_sd=sd(relabun[diet=="Wild"]*100, na.rm=T),
Pre_grass_mean=mean(relabun[diet=="Pre_grass"]*100, na.rm=T),
Pre_grass_sd=sd(relabun[diet=="Pre_grass"]*100, na.rm=T),
Post_grass_mean=mean(relabun[diet=="Post_grass"]*100, na.rm=T),
Post_grass_sd=sd(relabun[diet=="Post_grass"]*100, na.rm=T)) %>%
mutate(total=str_c(round(total_mean,2),"±",round(total_sd,2)),
Wild=str_c(round(Wild_mean,2),"±",round(Wild_sd,2)),
Pre_grass=str_c(round(Pre_grass_mean,6),"±",round(Pre_grass_sd,6)),
Post_grass=str_c(round(Post_grass_mean,2),"±",round(Post_grass_sd,2))) %>%
arrange(-total_mean) %>%
dplyr::select(phylum,total,Wild,Pre_grass,Post_grass)# A tibble: 15 × 5
phylum total Wild Pre_grass Post_grass
<chr> <chr> <chr> <chr> <chr>
1 p__Bacillota_A 57.24±12.62 48.64±13.52 59.845932±10.725422 63.25±9.01
2 p__Bacteroidota 25.79±10.11 26.89±11.81 24.986055±10.082621 25.49±9.07
3 p__Bacillota 4.12±7.2 5.07±11.15 4.94862±5.296738 2.34±2.73
4 p__Spirochaetota 3.91±10.01 11.73±14.79 0.00063±0.000727 0±0
5 p__Verrucomicrobiota 2.26±5.72 1.47±0.71 1.448674±1.294628 3.87±9.89
6 p__Pseudomonadota 1.63±3.33 0.51±0.4 3.082488±5.382343 1.29±1.52
7 p__Patescibacteria 0.99±1.54 0.21±0.25 2.176993±2.223404 0.57±0.41
8 p__Synergistota 0.96±0.85 1.86±0.83 0.449802±0.390105 0.57±0.35
9 p__Bacillota_C 0.84±0.79 1.7±0.67 0.385614±0.359883 0.45±0.49
10 p__Actinomycetota 0.78±0.99 0.43±0.46 1.217389±1.147372 0.7±1.1
11 p__Cyanobacteriota 0.71±2.08 0.28±0.61 0.915635±3.024426 0.93±1.99
12 p__Desulfobacterota 0.59±0.4 0.99±0.31 0.410146±0.255958 0.36±0.25
13 p__Bacillota_B 0.1±0.15 0.23±0.2 0.041532±0.023962 0.04±0.02
14 p__Methanobacteriota 0.08±0.22 0±0 0.090366±0.227643 0.15±0.29
15 p__Campylobacterota 0±0 0±0 0.000127±0.000226 0±0
phylum_arrange <- phylum_summary %>%
group_by(phylum) %>%
summarise(mean=sum(relabun)) %>%
arrange(-mean) %>%
select(phylum) %>%
pull()
phylum_summary %>%
left_join(genome_metadata %>% select(phylum,phylum) %>% unique(),by=join_by(phylum==phylum)) %>%
# left_join(sample_metadata,by=join_by(sample==sample)) %>%
filter(phylum %in% phylum_arrange[1:20]) %>%
mutate(phylum=factor(phylum,levels=rev(phylum_arrange[1:20]))) %>%
filter(relabun > 0) %>%
ggplot(aes(x=relabun, y=phylum, group=phylum, color=phylum)) +
scale_color_manual(values=phylum_colors[-8]) +
geom_jitter(alpha=0.5) +
facet_grid(.~diet)+
theme_minimal() +
labs(y="phylum", x="Relative abundance", color="Phylum")5.4 Taxonomy boxplot
5.4.1 Family
family_summary <- genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS nornalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>% #reduce to minimum number of columns
left_join(sample_metadata, by = join_by(sample == sample)) %>% #append sample metadata
left_join(., genome_metadata, by = join_by(genome == genome)) %>% #append genome metadata
group_by(sample,family, diet,region) %>%
summarise(relabun=sum(count))
family_summary$diet <- factor(family_summary$diet, levels=c("Pre_grass", "Post_grass", "Wild"))5.4.1.1 Origin: Wild vs Captive
family_summary %>%
group_by(family) %>%
summarise(total_mean=mean(relabun*100, na.rm=T),
total_sd=sd(relabun*100, na.rm=T),
Wild_mean=mean(relabun[diet=="Wild"]*100, na.rm=T),
Wild_sd=sd(relabun[diet=="Wild"]*100, na.rm=T),
Cap_mean=mean(relabun[region=="Nafarroa"]*100, na.rm=T),
Cap_sd=sd(relabun[region=="Nafarroa"]*100, na.rm=T)) %>%
mutate(Total=str_c(round(total_mean,2),"±",round(total_sd,2)),
Wild=str_c(round(Wild_mean,2),"±",round(Wild_sd,2)),
Captive=str_c(round(Cap_mean,2),"±",round(Cap_sd,2))) %>%
arrange(-total_mean) %>%
dplyr::select(family,Total,Wild,Captive) %>%
tt()| family | Total | Wild | Captive |
|---|---|---|---|
| f__Lachnospiraceae | 21.69±9.91 | 18.46±10.79 | 23.3±9.26 |
| f__Bacteroidaceae | 17.22±8.91 | 18.2±9.79 | 16.73±8.61 |
| f__Ruminococcaceae | 10.01±7.82 | 9.16±9.9 | 10.44±6.76 |
| f__Oscillospiraceae | 7.11±4.79 | 9.05±6.73 | 6.14±3.21 |
| f__Borkfalkiaceae | 4.87±7.57 | 1.52±3.18 | 6.55±8.57 |
| f__Sphaerochaetaceae | 3.91±10.01 | 11.73±14.79 | 0±0 |
| f__CAG-508 | 3.24±3.94 | 0.45±0.37 | 4.63±4.19 |
| f__Marinifilaceae | 2.49±1.42 | 3.1±1.62 | 2.19±1.23 |
| f__CAG-74 | 2.47±2.63 | 4.7±3.41 | 1.36±1.04 |
| f__UBA660 | 2.26±3.79 | 0.05±0.06 | 3.37±4.25 |
| f__Acutalibacteraceae | 2.14±1.03 | 1.88±1.17 | 2.28±0.95 |
| f__Rikenellaceae | 2.01±1.42 | 2.02±1.9 | 2.01±1.17 |
| f__CAG-314 | 1.89±4.51 | 0.04±0.03 | 2.81±5.32 |
| f__CAG-449 | 1.69±6.7 | 5.02±11.16 | 0.02±0.06 |
| f__Muribaculaceae | 1.33±1.73 | 0.28±0.48 | 1.85±1.9 |
| f__UBA932 | 1.26±2.12 | 2.09±3.28 | 0.84±1.06 |
| f__Victivallaceae | 1.23±0.94 | 1.41±0.75 | 1.15±1.02 |
| f__Tannerellaceae | 1.2±0.61 | 1.12±0.79 | 1.25±0.5 |
| f__Nanosyncoccaceae | 0.99±1.54 | 0.21±0.25 | 1.37±1.77 |
| f__Akkermansiaceae | 0.97±5.81 | 0±0 | 1.45±7.12 |
| f__Selenomonadaceae | 0.73±0.81 | 1.69±0.67 | 0.24±0.23 |
| f__Gastranaerophilaceae | 0.71±2.08 | 0.28±0.61 | 0.92±2.5 |
| f__CAG-274 | 0.67±0.66 | 0.8±0.64 | 0.6±0.68 |
| f__Dethiosulfovibrionaceae | 0.59±0.56 | 1.25±0.44 | 0.25±0.19 |
| f__Desulfovibrionaceae | 0.59±0.4 | 0.99±0.31 | 0.38±0.25 |
| f__Atopobiaceae | 0.53±0.85 | 0.2±0.23 | 0.69±0.99 |
| f__Burkholderiaceae_A | 0.51±0.39 | 0.46±0.39 | 0.54±0.4 |
| f__CAG-239 | 0.49±1.84 | 0.03±0.1 | 0.72±2.23 |
| f__CAG-917 | 0.42±0.68 | 0±0 | 0.63±0.75 |
| f__Monoglobaceae | 0.41±0.38 | 0.23±0.39 | 0.49±0.35 |
| f__Synergistaceae | 0.37±0.41 | 0.61±0.52 | 0.26±0.29 |
| f__UMGS1883 | 0.37±0.41 | 0.19±0.29 | 0.46±0.43 |
| f__UBA1381 | 0.36±0.31 | 0.37±0.22 | 0.35±0.35 |
| f__UBA1242 | 0.34±0.65 | 0.12±0.13 | 0.46±0.77 |
| f__Anaerovoracaceae | 0.23±0.36 | 0.65±0.35 | 0.02±0.03 |
| f__Eggerthellaceae | 0.23±0.21 | 0.23±0.24 | 0.22±0.19 |
| f__CAG-272 | 0.22±0.28 | 0.03±0.02 | 0.32±0.3 |
| f__Pumilibacteraceae | 0.21±0.39 | 0.02±0.03 | 0.31±0.45 |
| f__Burkholderiaceae_C | 0.18±1 | 0±0 | 0.26±1.22 |
| f__Butyricicoccaceae | 0.15±0.47 | 0.43±0.76 | 0.01±0.02 |
| f__UBA1820 | 0.14±0.15 | 0.08±0.09 | 0.17±0.16 |
| f__JAAYOS01 | 0.13±0.18 | 0.05±0.07 | 0.17±0.2 |
| f__Acidaminococcaceae | 0.12±0.38 | 0±0 | 0.18±0.45 |
| f__Flavobacteriaceae | 0.1±0.57 | 0±0 | 0.14±0.7 |
| f__Halomonadaceae | 0.09±0.29 | 0±0 | 0.14±0.35 |
| f__ | 0.08±0.21 | 0.17±0.28 | 0.04±0.15 |
| f__Wohlfahrtiimonadaceae | 0.08±0.48 | 0±0 | 0.12±0.58 |
| f__Methanobacteriaceae | 0.08±0.22 | 0±0 | 0.12±0.26 |
| f__UBA644 | 0.08±0.15 | 0.02±0.06 | 0.11±0.18 |
| f__Pseudomonadaceae | 0.07±0.41 | 0±0.01 | 0.11±0.5 |
| f__Alteromonadaceae | 0.07±0.24 | 0.02±0.04 | 0.1±0.29 |
| f__Xanthomonadaceae | 0.07±0.24 | 0±0 | 0.1±0.29 |
| f__Erysipelotrichaceae | 0.07±0.15 | 0±0 | 0.1±0.18 |
| f__UBA7702 | 0.06±0.11 | 0.12±0.17 | 0.03±0.02 |
| f__UBA1829 | 0.06±0.12 | 0.06±0.17 | 0.06±0.08 |
| f__UBA1750 | 0.06±0.11 | 0.15±0.16 | 0.01±0.03 |
| f__Salinicoccaceae | 0.06±0.19 | 0±0 | 0.09±0.22 |
| f__Eubacteriaceae | 0.05±0.1 | 0.1±0.15 | 0.02±0.04 |
| f__Aeromonadaceae | 0.05±0.27 | 0±0 | 0.07±0.33 |
| f__Peptococcaceae | 0.04±0.06 | 0.1±0.07 | 0.01±0.01 |
| f__Balneolaceae | 0.03±0.14 | 0±0 | 0.05±0.17 |
| f__Staphylococcaceae | 0.03±0.12 | 0±0 | 0.04±0.14 |
| f__Mycobacteriaceae | 0.03±0.06 | 0±0 | 0.04±0.07 |
| f__Anaerotignaceae | 0.02±0.04 | 0.06±0.05 | 0±0.01 |
| f__Oleiphilaceae | 0.02±0.08 | 0±0 | 0.03±0.1 |
| f__Coprobacillaceae | 0.02±0.1 | 0±0 | 0.03±0.12 |
| f__CAG-382 | 0.01±0.04 | 0±0 | 0.01±0.05 |
| f__Weeksellaceae | 0±0 | 0±0 | 0±0 |
| f__Neisseriaceae | 0±0 | 0±0 | 0±0 |
| f__Streptococcaceae | 0±0 | 0±0 | 0±0 |
| f__Helicobacteraceae | 0±0 | 0±0 | 0±0 |
| f__Moraxellaceae | 0±0 | 0±0 | 0±0 |
| f__Pasteurellaceae | 0±0 | 0±0 | 0±0 |
| f__UBA2023 | 0±0 | 0±0 | 0±0 |
| f__Cardiobacteriaceae | 0±0 | 0±0 | 0±0 |
5.4.1.2 Origin and Diet
family_summary %>%
group_by(family) %>%
summarise(total_mean=mean(relabun*100, na.rm=T),
total_sd=sd(relabun*100, na.rm=T),
Wild_mean=mean(relabun[diet=="Wild"]*100, na.rm=T),
Wild_sd=sd(relabun[diet=="Wild"]*100, na.rm=T),
Pre_grass_mean=mean(relabun[diet=="Pre_grass"]*100, na.rm=T),
Pre_grass_sd=sd(relabun[diet=="Pre_grass"]*100, na.rm=T),
Post_grass_mean=mean(relabun[diet=="Post_grass"]*100, na.rm=T),
Post_grass_sd=sd(relabun[diet=="Post_grass"]*100, na.rm=T)) %>%
mutate(Total=str_c(round(total_mean,2),"±",round(total_sd,2)),
Wild=str_c(round(Wild_mean,2),"±",round(Wild_sd,2)),
Pre_grass=str_c(round(Pre_grass_mean,2),"±",round(Pre_grass_sd,2)),
Post_grass=str_c(round(Post_grass_mean,2),"±",round(Post_grass_sd,2))) %>%
arrange(-total_mean) %>%
dplyr::select(family,Total,Wild,Pre_grass,Post_grass) %>%
tt()| family | Total | Wild | Pre_grass | Post_grass |
|---|---|---|---|---|
| f__Lachnospiraceae | 21.69±9.91 | 18.46±10.79 | 23.69±8.7 | 22.91±10.16 |
| f__Bacteroidaceae | 17.22±8.91 | 18.2±9.79 | 16.79±9.7 | 16.68±7.82 |
| f__Ruminococcaceae | 10.01±7.82 | 9.16±9.9 | 11.75±8.53 | 9.12±4.36 |
| f__Oscillospiraceae | 7.11±4.79 | 9.05±6.73 | 5.21±2.15 | 7.08±3.87 |
| f__Borkfalkiaceae | 4.87±7.57 | 1.52±3.18 | 4.6±5.72 | 8.49±10.62 |
| f__Sphaerochaetaceae | 3.91±10.01 | 11.73±14.79 | 0±0 | 0±0 |
| f__CAG-508 | 3.24±3.94 | 0.45±0.37 | 5.81±4.22 | 3.46±3.98 |
| f__Marinifilaceae | 2.49±1.42 | 3.1±1.62 | 2.11±1.3 | 2.27±1.21 |
| f__CAG-74 | 2.47±2.63 | 4.7±3.41 | 1.03±0.72 | 1.68±1.24 |
| f__UBA660 | 2.26±3.79 | 0.05±0.06 | 4.57±5.23 | 2.17±2.7 |
| f__Acutalibacteraceae | 2.14±1.03 | 1.88±1.17 | 2.3±0.79 | 2.26±1.13 |
| f__Rikenellaceae | 2.01±1.42 | 2.02±1.9 | 2.14±1.45 | 1.88±0.83 |
| f__CAG-314 | 1.89±4.51 | 0.04±0.03 | 1.54±2.53 | 4.08±7.01 |
| f__CAG-449 | 1.69±6.7 | 5.02±11.16 | 0.03±0.08 | 0±0 |
| f__Muribaculaceae | 1.33±1.73 | 0.28±0.48 | 1.23±1.33 | 2.46±2.22 |
| f__UBA932 | 1.26±2.12 | 2.09±3.28 | 1.04±1.21 | 0.65±0.9 |
| f__Victivallaceae | 1.23±0.94 | 1.41±0.75 | 1.38±1.25 | 0.91±0.71 |
| f__Tannerellaceae | 1.2±0.61 | 1.12±0.79 | 1.17±0.58 | 1.32±0.42 |
| f__Nanosyncoccaceae | 0.99±1.54 | 0.21±0.25 | 2.18±2.22 | 0.57±0.41 |
| f__Akkermansiaceae | 0.97±5.81 | 0±0 | 0±0 | 2.9±10.06 |
| f__Selenomonadaceae | 0.73±0.81 | 1.69±0.67 | 0.21±0.19 | 0.27±0.28 |
| f__Gastranaerophilaceae | 0.71±2.08 | 0.28±0.61 | 0.92±3.02 | 0.93±1.99 |
| f__CAG-274 | 0.67±0.66 | 0.8±0.64 | 0.59±0.5 | 0.62±0.84 |
| f__Dethiosulfovibrionaceae | 0.59±0.56 | 1.25±0.44 | 0.19±0.15 | 0.32±0.21 |
| f__Desulfovibrionaceae | 0.59±0.4 | 0.99±0.31 | 0.41±0.26 | 0.36±0.25 |
| f__Atopobiaceae | 0.53±0.85 | 0.2±0.23 | 0.88±0.98 | 0.51±1 |
| f__Burkholderiaceae_A | 0.51±0.39 | 0.46±0.39 | 0.6±0.52 | 0.47±0.24 |
| f__CAG-239 | 0.49±1.84 | 0.03±0.1 | 0.99±3.04 | 0.44±1 |
| f__CAG-917 | 0.42±0.68 | 0±0 | 0.61±0.76 | 0.66±0.77 |
| f__Monoglobaceae | 0.41±0.38 | 0.23±0.39 | 0.56±0.39 | 0.42±0.3 |
| f__Synergistaceae | 0.37±0.41 | 0.61±0.52 | 0.26±0.38 | 0.25±0.17 |
| f__UMGS1883 | 0.37±0.41 | 0.19±0.29 | 0.31±0.29 | 0.6±0.51 |
| f__UBA1381 | 0.36±0.31 | 0.37±0.22 | 0.3±0.37 | 0.41±0.33 |
| f__UBA1242 | 0.34±0.65 | 0.12±0.13 | 0.41±0.58 | 0.5±0.94 |
| f__Anaerovoracaceae | 0.23±0.36 | 0.65±0.35 | 0.02±0.02 | 0.02±0.03 |
| f__Eggerthellaceae | 0.23±0.21 | 0.23±0.24 | 0.29±0.22 | 0.16±0.13 |
| f__CAG-272 | 0.22±0.28 | 0.03±0.02 | 0.42±0.39 | 0.21±0.13 |
| f__Pumilibacteraceae | 0.21±0.39 | 0.02±0.03 | 0.25±0.29 | 0.37±0.57 |
| f__Burkholderiaceae_C | 0.18±1 | 0±0 | 0.53±1.72 | 0±0.01 |
| f__Butyricicoccaceae | 0.15±0.47 | 0.43±0.76 | 0.01±0.01 | 0.02±0.02 |
| f__UBA1820 | 0.14±0.15 | 0.08±0.09 | 0.2±0.19 | 0.15±0.13 |
| f__JAAYOS01 | 0.13±0.18 | 0.05±0.07 | 0.21±0.25 | 0.14±0.15 |
| f__Acidaminococcaceae | 0.12±0.38 | 0±0 | 0.17±0.41 | 0.18±0.51 |
| f__Flavobacteriaceae | 0.1±0.57 | 0±0 | 0.28±0.98 | 0±0 |
| f__Halomonadaceae | 0.09±0.29 | 0±0 | 0.15±0.36 | 0.13±0.36 |
| f__ | 0.08±0.21 | 0.17±0.28 | 0.07±0.21 | 0.01±0.01 |
| f__Wohlfahrtiimonadaceae | 0.08±0.48 | 0±0 | 0.25±0.82 | 0±0 |
| f__Methanobacteriaceae | 0.08±0.22 | 0±0 | 0.09±0.23 | 0.15±0.29 |
| f__UBA644 | 0.08±0.15 | 0.02±0.06 | 0.09±0.05 | 0.14±0.25 |
| f__Pseudomonadaceae | 0.07±0.41 | 0±0.01 | 0.21±0.71 | 0.01±0.01 |
| f__Alteromonadaceae | 0.07±0.24 | 0.02±0.04 | 0.12±0.38 | 0.08±0.18 |
| f__Xanthomonadaceae | 0.07±0.24 | 0±0 | 0.06±0.16 | 0.14±0.38 |
| f__Erysipelotrichaceae | 0.07±0.15 | 0±0 | 0.11±0.18 | 0.09±0.18 |
| f__UBA7702 | 0.06±0.11 | 0.12±0.17 | 0.03±0.02 | 0.04±0.02 |
| f__UBA1829 | 0.06±0.12 | 0.06±0.17 | 0.07±0.1 | 0.06±0.06 |
| f__UBA1750 | 0.06±0.11 | 0.15±0.16 | 0.01±0.01 | 0.02±0.04 |
| f__Salinicoccaceae | 0.06±0.19 | 0±0 | 0.1±0.31 | 0.07±0.09 |
| f__Eubacteriaceae | 0.05±0.1 | 0.1±0.15 | 0.04±0.05 | 0±0.01 |
| f__Aeromonadaceae | 0.05±0.27 | 0±0 | 0.14±0.46 | 0±0 |
| f__Peptococcaceae | 0.04±0.06 | 0.1±0.07 | 0.01±0.01 | 0.01±0.01 |
| f__Balneolaceae | 0.03±0.14 | 0±0 | 0.02±0.08 | 0.07±0.23 |
| f__Staphylococcaceae | 0.03±0.12 | 0±0 | 0.08±0.2 | 0.01±0.02 |
| f__Mycobacteriaceae | 0.03±0.06 | 0±0 | 0.05±0.08 | 0.04±0.05 |
| f__Anaerotignaceae | 0.02±0.04 | 0.06±0.05 | 0±0.01 | 0.01±0.01 |
| f__Oleiphilaceae | 0.02±0.08 | 0±0 | 0.04±0.13 | 0.02±0.03 |
| f__Coprobacillaceae | 0.02±0.1 | 0±0 | 0.05±0.17 | 0±0 |
| f__CAG-382 | 0.01±0.04 | 0±0 | 0.02±0.08 | 0±0.01 |
| f__Weeksellaceae | 0±0 | 0±0 | 0±0 | 0±0 |
| f__Neisseriaceae | 0±0 | 0±0 | 0±0 | 0±0 |
| f__Streptococcaceae | 0±0 | 0±0 | 0±0 | 0±0 |
| f__Helicobacteraceae | 0±0 | 0±0 | 0±0 | 0±0 |
| f__Moraxellaceae | 0±0 | 0±0 | 0±0 | 0±0 |
| f__Pasteurellaceae | 0±0 | 0±0 | 0±0 | 0±0 |
| f__UBA2023 | 0±0 | 0±0 | 0±0 | 0±0 |
| f__Cardiobacteriaceae | 0±0 | 0±0 | 0±0 | 0±0 |
family_arrange <- family_summary %>%
group_by(family) %>%
summarise(mean=sum(relabun)) %>%
arrange(-mean) %>%
select(family) %>%
pull()
family_summary %>%
left_join(genome_metadata %>% select(family,phylum) %>% unique(),by=join_by(family==family)) %>%
filter(family %in% family_arrange[1:20]) %>%
mutate(family=factor(family,levels=rev(family_arrange[1:20]))) %>%
filter(relabun > 0) %>%
ggplot(aes(x=relabun, y=family, group=family, color=phylum)) +
scale_color_manual(values=phylum_colors[-8]) +
geom_jitter(alpha=0.5) +
facet_grid(.~diet)+
theme_minimal() +
labs(y="Family", x="Relative abundance", color="Phylum")5.4.2 Genus
genus_summary <- genome_counts_filt %>%
mutate_at(vars(-genome),~./sum(.)) %>% #apply TSS nornalisation
pivot_longer(-genome, names_to = "sample", values_to = "count") %>% #reduce to minimum number of columns
left_join(sample_metadata, by = join_by(sample == sample)) %>% #append sample metadata
left_join(genome_metadata, by = join_by(genome == genome)) %>% #append genome metadata
group_by(sample,phylum,genus, diet) %>%
summarise(relabun=sum(count)) %>%
filter(genus != "g__") %>%
mutate(genus= sub("^g__", "", genus))
genus_summary$diet <- factor(genus_summary$diet, levels=c("Pre_grass", "Post_grass", "Wild"))5.4.3 origin and diet
genus_summary %>%
group_by(genus) %>%
summarise(total_mean=mean(relabun*100, na.rm=T),
total_sd=sd(relabun*100, na.rm=T),
Wild_mean=mean(relabun[diet=="Wild"]*100, na.rm=T),
Wild_sd=sd(relabun[diet=="Wild"]*100, na.rm=T),
Pre_grass_mean=mean(relabun[diet=="Pre_grass"]*100, na.rm=T),
Pre_grass_sd=sd(relabun[diet=="Pre_grass"]*100, na.rm=T),
Post_grass_mean=mean(relabun[diet=="Post_grass"]*100, na.rm=T),
Post_grass_sd=sd(relabun[diet=="Post_grass"]*100, na.rm=T)) %>%
mutate(Total=str_c(round(total_mean,2),"±",round(total_sd,2)),
Wild=str_c(round(Wild_mean,2),"±",round(Wild_sd,2)),
Pre_grass=str_c(round(Pre_grass_mean,2),"±",round(Pre_grass_sd,2)),
Post_grass=str_c(round(Post_grass_mean,2),"±",round(Post_grass_sd,2))) %>%
arrange(-total_mean) %>%
dplyr::select(genus,Total,Wild,Pre_grass,Post_grass) %>%
tt()| genus | Total | Wild | Pre_grass | Post_grass |
|---|---|---|---|---|
| Bacteroides | 11.45±7.42 | 10.71±8.63 | 12.01±7.78 | 11.63±6.26 |
| Eisenbergiella | 9.15±9.45 | 4.11±11.28 | 11.85±6.46 | 11.49±8.57 |
| Phocaeicola | 4.75±2.03 | 5.26±2.32 | 4.37±2.02 | 4.64±1.78 |
| UBA9732 | 3.91±10.01 | 11.73±14.79 | 0±0 | 0±0 |
| Coproplasma | 2.59±5.68 | 0.67±2.29 | 2.05±3.56 | 5.05±8.59 |
| Gallimonas | 2.28±4.19 | 0.85±2.4 | 2.55±3.63 | 3.44±5.77 |
| UBA7477 | 2.17±5.94 | 0.02±0.01 | 4.95±9.5 | 1.54±2.86 |
| CAJOIG01 | 1.97±1.72 | 2.73±1.76 | 1.42±1.39 | 1.77±1.82 |
| Alistipes | 1.84±1.42 | 1.93±1.94 | 1.91±1.43 | 1.68±0.74 |
| Fimimonas | 1.83±4.48 | 0.03±0.03 | 1.47±2.55 | 4±6.97 |
| Enterenecus | 1.78±2.42 | 3.34±3.63 | 0.76±0.38 | 1.23±1.07 |
| UBA1366 | 1.36±1.8 | 0.27±0.18 | 1.68±2.05 | 2.13±2 |
| Ruminococcus_D | 1.3±1.55 | 0.24±0.28 | 1.85±1.89 | 1.81±1.47 |
| CAG-269 | 1.3±1.53 | 0.21±0.17 | 2.39±1.62 | 1.29±1.47 |
| Egerieousia | 1.26±2.12 | 2.09±3.28 | 1.04±1.21 | 0.65±0.9 |
| Gabonibacter | 1.24±0.78 | 1.74±0.87 | 0.95±0.58 | 1.04±0.64 |
| Odoribacter | 1.22±0.94 | 1.36±1.26 | 1.11±0.8 | 1.2±0.72 |
| Parabacteroides | 1.2±0.61 | 1.12±0.79 | 1.17±0.58 | 1.32±0.42 |
| Choladousia | 1.17±1.12 | 1.77±1.17 | 0.68±0.86 | 1.05±1.09 |
| UBA3402 | 1.1±0.68 | 1.13±0.61 | 1.12±0.74 | 1.05±0.74 |
| Nanosyncoccus | 0.99±1.54 | 0.21±0.25 | 2.18±2.22 | 0.57±0.41 |
| Akkermansia | 0.97±5.81 | 0±0 | 0±0 | 2.9±10.06 |
| Merdiplasma | 0.96±1.7 | 2.87±1.81 | 0.01±0.01 | 0.01±0.01 |
| COE1 | 0.95±1.32 | 0.75±2.06 | 1.17±0.92 | 0.93±0.55 |
| UBA3282 | 0.9±1.95 | 0.04±0.03 | 0.84±1.31 | 1.81±2.95 |
| Blautia_A | 0.86±1.19 | 1.48±1.84 | 0.5±0.36 | 0.6±0.6 |
| RUG626 | 0.82±1.2 | 0.17±0.25 | 1.12±1.01 | 1.19±1.68 |
| V9D3004 | 0.82±1.18 | 1.1±1.85 | 0.7±0.62 | 0.66±0.71 |
| Ventricola | 0.81±0.91 | 0.84±0.69 | 0.51±0.5 | 1.08±1.32 |
| Victivallis | 0.79±0.65 | 1.03±0.58 | 0.84±0.82 | 0.5±0.42 |
| MGBC124762 | 0.78±1.48 | 1.46±2.23 | 0.28±0.42 | 0.59±0.99 |
| Fimenecus | 0.64±0.77 | 0.2±0.52 | 1.11±0.9 | 0.62±0.61 |
| Pyramidobacter | 0.59±0.56 | 1.25±0.44 | 0.19±0.15 | 0.32±0.21 |
| Stercorousia | 0.58±1.99 | 0.18±0.57 | 0.89±3.02 | 0.67±1.69 |
| CAG-485 | 0.56±0.61 | 0.23±0.48 | 0.56±0.62 | 0.9±0.56 |
| Paraprevotella | 0.55±1.81 | 1.42±3.02 | 0.16±0.2 | 0.08±0.05 |
| Parasutterella | 0.51±0.39 | 0.46±0.39 | 0.6±0.52 | 0.47±0.24 |
| Mailhella | 0.46±0.41 | 0.92±0.32 | 0.23±0.19 | 0.22±0.21 |
| CALXXL01 | 0.44±0.39 | 0.38±0.28 | 0.54±0.52 | 0.41±0.34 |
| Avilachnospira | 0.44±0.99 | 1.31±1.36 | 0±0 | 0.02±0.04 |
| Choladocola | 0.44±0.55 | 0.22±0.6 | 0.59±0.58 | 0.5±0.45 |
| Ruminococcus | 0.43±0.62 | 0.33±0.33 | 0.34±0.27 | 0.61±0.99 |
| CAG-590 | 0.42±0.94 | 0.04±0.09 | 0.75±1.28 | 0.47±0.94 |
| Roseburia | 0.42±0.87 | 0.08±0.11 | 0.43±0.67 | 0.73±1.31 |
| UBA3855 | 0.41±0.57 | 0.29±0.65 | 0.34±0.39 | 0.6±0.64 |
| HGM10766 | 0.41±2.16 | 0±0 | 1.19±3.72 | 0.02±0.03 |
| Monoglobus | 0.41±0.38 | 0.23±0.39 | 0.56±0.39 | 0.42±0.3 |
| MGBC105563 | 0.4±0.77 | 0.12±0.24 | 0.63±0.89 | 0.43±0.94 |
| UMGS1601 | 0.4±0.65 | 0.15±0.29 | 0.32±0.37 | 0.72±0.97 |
| Pelethomonas | 0.39±0.43 | 0.27±0.63 | 0.35±0.21 | 0.54±0.31 |
| Scatovivens | 0.38±0.94 | 0±0 | 0.86±1.45 | 0.28±0.56 |
| Caccocola | 0.37±0.41 | 0.61±0.52 | 0.26±0.38 | 0.25±0.17 |
| Gemmiger | 0.37±0.92 | 0.53±1.18 | 0.36±1.04 | 0.21±0.42 |
| Phocaeicola_A | 0.35±0.34 | 0.5±0.45 | 0.24±0.19 | 0.32±0.31 |
| CAG-452 | 0.34±0.93 | 0.02±0.03 | 0.86±1.48 | 0.15±0.32 |
| Muribaculum | 0.34±1.08 | 0.01±0.01 | 0.4±1.09 | 0.6±1.53 |
| UMGS1663 | 0.34±0.87 | 0.05±0.04 | 0.6±1.29 | 0.37±0.73 |
| 14-2 | 0.32±1.87 | 0±0.01 | 0.94±3.24 | 0.01±0 |
| CAJMNU01 | 0.3±1.8 | 0±0 | 0.9±3.12 | 0.01±0 |
| UBA1213 | 0.3±0.54 | 0.09±0.24 | 0.27±0.31 | 0.54±0.82 |
| UBA6857 | 0.29±0.41 | 0.7±0.51 | 0.08±0.05 | 0.08±0.04 |
| UBA1224 | 0.29±0.73 | 0.85±1.09 | 0.01±0.01 | 0.01±0.01 |
| CALWRD01 | 0.29±0.32 | 0.06±0.09 | 0.39±0.34 | 0.41±0.35 |
| Paramuribaculum | 0.26±0.38 | 0.04±0.02 | 0.26±0.25 | 0.49±0.52 |
| JAJQCX01 | 0.25±0.32 | 0.02±0.01 | 0.24±0.22 | 0.49±0.39 |
| Marvinbryantia | 0.25±0.35 | 0.06±0.02 | 0.42±0.43 | 0.26±0.38 |
| SIG200 | 0.23±0.79 | 0±0 | 0.54±1.29 | 0.16±0.41 |
| SFTH01 | 0.23±0.35 | 0.47±0.5 | 0.11±0.11 | 0.1±0.14 |
| Aphodocola | 0.22±0.79 | 0±0 | 0.61±1.3 | 0.06±0.18 |
| Limadaptatus | 0.21±0.49 | 0±0 | 0.38±0.7 | 0.26±0.41 |
| CAG-475 | 0.21±0.52 | 0±0 | 0.23±0.51 | 0.39±0.72 |
| Copromonas | 0.21±0.22 | 0.24±0.32 | 0.13±0.12 | 0.25±0.18 |
| CAG-95 | 0.21±0.97 | 0.01±0.01 | 0.07±0.05 | 0.54±1.67 |
| Schaedlerella | 0.2±0.47 | 0.02±0.01 | 0.15±0.15 | 0.44±0.75 |
| Lawsonibacter | 0.2±0.26 | 0.39±0.27 | 0.09±0.2 | 0.11±0.22 |
| Eubacterium_R | 0.19±0.34 | 0.03±0.01 | 0.32±0.39 | 0.24±0.4 |
| RGIG2066 | 0.19±0.4 | 0.58±0.51 | 0±0 | 0±0 |
| CAG-552 | 0.19±0.31 | 0.01±0.03 | 0.25±0.29 | 0.29±0.41 |
| CAG-353 | 0.18±0.86 | 0±0 | 0.41±1.42 | 0.14±0.48 |
| Acetatifactor | 0.18±0.21 | 0.06±0.04 | 0.26±0.31 | 0.23±0.15 |
| RUG115 | 0.18±0.47 | 0.34±0.8 | 0.12±0.08 | 0.09±0.06 |
| Marseille-P3106 | 0.17±0.37 | 0.02±0.04 | 0.22±0.3 | 0.28±0.55 |
| Alistipes_A | 0.17±0.12 | 0.09±0.08 | 0.23±0.1 | 0.2±0.13 |
| UMGS2069 | 0.17±0.18 | 0.12±0.14 | 0.21±0.27 | 0.17±0.11 |
| Dysosmobacter | 0.16±0.16 | 0.24±0.22 | 0.13±0.12 | 0.12±0.08 |
| Duncaniella | 0.16±0.93 | 0±0 | 0.01±0.02 | 0.48±1.61 |
| Eubacterium_I | 0.16±0.28 | 0.44±0.35 | 0.01±0.01 | 0.02±0.03 |
| Eubacterium_G | 0.15±0.27 | 0.01±0.01 | 0.28±0.39 | 0.17±0.2 |
| Pseudoruminococcus | 0.15±0.34 | 0±0 | 0.2±0.37 | 0.26±0.43 |
| Ventrimonas | 0.15±0.27 | 0.29±0.37 | 0.12±0.24 | 0.03±0.02 |
| UMGS995 | 0.15±0.52 | 0±0 | 0.4±0.87 | 0.04±0.07 |
| Paenalcaligenes | 0.14±0.81 | 0±0 | 0.43±1.4 | 0±0.01 |
| Merdimorpha | 0.14±0.15 | 0.08±0.09 | 0.2±0.19 | 0.15±0.13 |
| CAG-103 | 0.14±0.49 | 0±0 | 0.13±0.39 | 0.3±0.75 |
| MGBC163016 | 0.14±0.15 | 0.05±0.04 | 0.23±0.19 | 0.15±0.13 |
| CAG-793 | 0.14±0.34 | 0.02±0.02 | 0.23±0.42 | 0.17±0.4 |
| RGIG3926 | 0.14±0.35 | 0.41±0.53 | 0±0 | 0±0 |
| CAG-41 | 0.14±0.26 | 0.03±0.05 | 0.19±0.35 | 0.19±0.27 |
| CALXFK01 | 0.13±0.18 | 0.05±0.07 | 0.21±0.25 | 0.14±0.15 |
| Onthocola_B | 0.13±0.42 | 0±0 | 0.38±0.68 | 0.01±0.02 |
| Butyricicoccus_A | 0.13±0.47 | 0.36±0.78 | 0.01±0.01 | 0.01±0.02 |
| Coprococcus | 0.13±0.33 | 0.01±0.02 | 0.11±0.09 | 0.27±0.55 |
| UBA5578 | 0.13±0.58 | 0±0.02 | 0.08±0.19 | 0.29±0.99 |
| Caccovivens | 0.12±0.36 | 0±0 | 0.2±0.44 | 0.18±0.43 |
| RUG11788 | 0.12±0.37 | 0±0 | 0.08±0.19 | 0.28±0.59 |
| CAG-266 | 0.12±0.38 | 0±0 | 0.17±0.41 | 0.18±0.51 |
| Mediterranea | 0.11±0.6 | 0.31±1.03 | 0.01±0.01 | 0.01±0.01 |
| Fimivicinus | 0.11±0.43 | 0.01±0.02 | 0.01±0 | 0.32±0.71 |
| Acutalibacter | 0.11±0.15 | 0.08±0.05 | 0.11±0.16 | 0.13±0.19 |
| UBA11774 | 0.1±0.37 | 0.26±0.62 | 0.03±0.02 | 0.02±0.02 |
| Hominisplanchenecus | 0.1±0.08 | 0.13±0.06 | 0.1±0.11 | 0.08±0.05 |
| CALXJL01 | 0.1±0.54 | 0±0 | 0.3±0.93 | 0.01±0.01 |
| Ventrenecus | 0.1±0.38 | 0±0 | 0.28±0.63 | 0.01±0.01 |
| Flavobacterium | 0.1±0.57 | 0±0 | 0.28±0.98 | 0±0 |
| Halomonas | 0.09±0.29 | 0±0 | 0.15±0.36 | 0.13±0.36 |
| UBA738 | 0.09±0.33 | 0.27±0.55 | 0±0 | 0.01±0 |
| JAAWPK01 | 0.09±0.27 | 0.12±0.26 | 0.13±0.39 | 0.03±0.05 |
| RGIG2774 | 0.09±0.3 | 0.25±0.49 | 0±0 | 0±0 |
| UBA3789 | 0.09±0.34 | 0±0 | 0.03±0.03 | 0.23±0.58 |
| UMGS973 | 0.08±0.17 | 0.22±0.24 | 0.01±0.02 | 0.02±0.03 |
| CALWPC01 | 0.08±0.17 | 0.19±0.26 | 0.04±0.05 | 0.02±0.01 |
| Methanosphaera | 0.08±0.22 | 0±0 | 0.09±0.23 | 0.15±0.29 |
| Geddesella | 0.08±0.15 | 0.02±0.06 | 0.09±0.05 | 0.14±0.25 |
| UMGS1124 | 0.08±0.44 | 0±0 | 0±0.01 | 0.23±0.76 |
| Butyribacter | 0.08±0.11 | 0.01±0.01 | 0.14±0.13 | 0.08±0.12 |
| Limivicinus | 0.08±0.21 | 0±0 | 0.07±0.16 | 0.15±0.31 |
| F23-B02 | 0.08±0.26 | 0±0 | 0.01±0.02 | 0.22±0.43 |
| Zag111 | 0.07±0.43 | 0±0 | 0±0.01 | 0.22±0.74 |
| Avispirillum | 0.07±0.11 | 0±0 | 0.13±0.15 | 0.08±0.07 |
| UBA11524 | 0.07±0.3 | 0±0 | 0.03±0.05 | 0.18±0.52 |
| Aliidiomarina | 0.07±0.24 | 0.02±0.04 | 0.12±0.38 | 0.08±0.18 |
| Thiopseudomonas | 0.07±0.41 | 0±0 | 0.21±0.71 | 0±0 |
| Faecousia | 0.07±0.25 | 0.01±0.01 | 0.19±0.42 | 0.01±0.01 |
| Ignatzschineria | 0.07±0.4 | 0±0 | 0.2±0.68 | 0±0 |
| Luteimonas_D | 0.07±0.24 | 0±0 | 0.06±0.16 | 0.14±0.38 |
| Cryptoclostridium | 0.06±0.11 | 0.12±0.17 | 0.03±0.02 | 0.04±0.02 |
| CAG-115 | 0.06±0.34 | 0±0 | 0.18±0.59 | 0±0 |
| UBA11452 | 0.06±0.12 | 0.06±0.17 | 0.07±0.1 | 0.06±0.06 |
| UBA1428 | 0.06±0.11 | 0.15±0.16 | 0.01±0.01 | 0.02±0.04 |
| RUG11130 | 0.06±0.15 | 0.02±0.02 | 0.12±0.25 | 0.04±0.03 |
| JAFLUQ01 | 0.06±0.18 | 0.17±0.29 | 0.01±0.01 | 0±0 |
| RUG14903 | 0.06±0.11 | 0.01±0.01 | 0.13±0.16 | 0.04±0.04 |
| CAG-273 | 0.06±0.24 | 0±0 | 0.15±0.41 | 0.01±0.02 |
| 12844 | 0.06±0.15 | 0.01±0.02 | 0.04±0.05 | 0.12±0.24 |
| Onthoplasma | 0.05±0.32 | 0±0 | 0±0 | 0.16±0.55 |
| Enterocloster | 0.05±0.09 | 0.06±0.15 | 0.05±0.05 | 0.05±0.05 |
| RUG591 | 0.05±0.3 | 0±0 | 0.15±0.53 | 0±0 |
| Heteroclostridium | 0.05±0.06 | 0.01±0.01 | 0.07±0.06 | 0.08±0.06 |
| UBA2882 | 0.05±0.27 | 0±0 | 0.14±0.47 | 0.02±0.06 |
| JAAWJJ01 | 0.05±0.12 | 0.15±0.17 | 0±0 | 0±0 |
| CAKSQF01 | 0.05±0.08 | 0±0 | 0.08±0.09 | 0.06±0.09 |
| Scatocola | 0.05±0.22 | 0.03±0.1 | 0.11±0.37 | 0±0 |
| Eubacterium_F | 0.05±0.12 | 0.01±0.01 | 0.1±0.19 | 0.04±0.07 |
| Ornithomonoglobus | 0.05±0.14 | 0.13±0.23 | 0.01±0.02 | 0±0.01 |
| Emergencia | 0.05±0.08 | 0.13±0.08 | 0±0 | 0±0 |
| UBA7067 | 0.05±0.1 | 0.02±0.05 | 0.05±0.08 | 0.06±0.15 |
| Oceanisphaera | 0.05±0.27 | 0±0 | 0.14±0.46 | 0±0 |
| Ruminococcus_E | 0.04±0.15 | 0.08±0.23 | 0.05±0.14 | 0.01±0.01 |
| RUG12438 | 0.04±0.18 | 0±0 | 0.03±0.07 | 0.1±0.3 |
| Caccovicinus | 0.04±0.21 | 0±0.01 | 0.11±0.36 | 0.01±0.01 |
| Ruminococcus_C | 0.04±0.08 | 0.03±0.1 | 0.05±0.05 | 0.04±0.09 |
| RGIG7179 | 0.04±0.08 | 0.12±0.09 | 0±0 | 0±0 |
| UBA7185 | 0.04±0.06 | 0.1±0.07 | 0.01±0.01 | 0.01±0.01 |
| UBA1066 | 0.04±0.09 | 0.12±0.12 | 0±0 | 0±0 |
| Ruminiclostridium_E | 0.04±0.18 | 0±0 | 0±0 | 0.11±0.31 |
| Blautia | 0.04±0.19 | 0±0 | 0.01±0.01 | 0.1±0.33 |
| RUG11890 | 0.04±0.14 | 0±0 | 0.04±0.07 | 0.07±0.23 |
| RUG762 | 0.04±0.17 | 0±0.01 | 0.09±0.3 | 0.01±0 |
| Faecalimonas | 0.03±0.11 | 0.1±0.17 | 0±0 | 0±0 |
| MGBC119817 | 0.03±0.07 | 0±0 | 0.07±0.11 | 0.03±0.05 |
| Scybalousia | 0.03±0.16 | 0±0 | 0.08±0.28 | 0.02±0.07 |
| Alangreenwoodia | 0.03±0.06 | 0.1±0.06 | 0±0 | 0±0 |
| Ruthenibacterium | 0.03±0.05 | 0±0.01 | 0.05±0.07 | 0.04±0.05 |
| UBA3818 | 0.03±0.05 | 0±0 | 0.03±0.02 | 0.07±0.06 |
| Jeotgalicoccus | 0.03±0.16 | 0±0 | 0.09±0.27 | 0.01±0.02 |
| Oligella | 0.03±0.18 | 0±0 | 0.09±0.32 | 0±0.01 |
| Coprovivens | 0.03±0.19 | 0±0 | 0±0 | 0.09±0.33 |
| UBA2664 | 0.03±0.14 | 0±0 | 0.02±0.08 | 0.07±0.23 |
| Bilophila | 0.03±0.02 | 0.05±0.02 | 0.02±0.01 | 0.02±0.01 |
| MGBC100174 | 0.03±0.06 | 0.03±0.07 | 0.02±0.03 | 0.04±0.06 |
| Avigastranaerophilus | 0.03±0.17 | 0.09±0.29 | 0±0 | 0±0 |
| Butyricimonas | 0.03±0.07 | 0.01±0 | 0.05±0.11 | 0.03±0.03 |
| Staphylococcus | 0.03±0.12 | 0±0 | 0.08±0.2 | 0.01±0.02 |
| Corynebacterium | 0.03±0.06 | 0±0 | 0.05±0.08 | 0.04±0.05 |
| RGIG3102 | 0.03±0.06 | 0.08±0.09 | 0±0 | 0±0 |
| JABUSF01 | 0.03±0.07 | 0±0 | 0.04±0.06 | 0.04±0.1 |
| Salinicoccus | 0.03±0.06 | 0±0 | 0.02±0.04 | 0.06±0.08 |
| Protoclostridium | 0.03±0.15 | 0±0 | 0±0 | 0.08±0.26 |
| QAKD01 | 0.03±0.08 | 0.08±0.12 | 0±0 | 0±0 |
| UBA3305 | 0.02±0.11 | 0.06±0.18 | 0.01±0.01 | 0.01±0 |
| RGIG1902 | 0.02±0.04 | 0.06±0.04 | 0±0 | 0±0 |
| Metalachnospira | 0.02±0.04 | 0.06±0.05 | 0±0.01 | 0.01±0.01 |
| CADBMC01 | 0.02±0.04 | 0.06±0.06 | 0.01±0.01 | 0±0.01 |
| Angelakisella | 0.02±0.05 | 0.07±0.06 | 0±0 | 0±0 |
| SIG32 | 0.02±0.04 | 0±0 | 0.02±0.02 | 0.04±0.06 |
| Faecivivens | 0.02±0.04 | 0.06±0.06 | 0±0 | 0±0 |
| MGBC108787 | 0.02±0.11 | 0±0 | 0±0 | 0.06±0.19 |
| Lachnoclostridium_B | 0.02±0.06 | 0±0 | 0.05±0.11 | 0.01±0.01 |
| TWA4 | 0.02±0.03 | 0.04±0.04 | 0.01±0.01 | 0.01±0.01 |
| CAKOLD01 | 0.02±0.1 | 0±0 | 0.06±0.16 | 0±0 |
| HGM12545 | 0.02±0.1 | 0±0 | 0.05±0.16 | 0.01±0.02 |
| Firm-04 | 0.02±0.08 | 0.04±0.14 | 0.01±0.02 | 0.01±0.01 |
| HGM13634 | 0.02±0.09 | 0±0 | 0.05±0.16 | 0.01±0.02 |
| Marinobacter | 0.02±0.08 | 0±0 | 0.04±0.13 | 0.02±0.03 |
| KLE1615 | 0.02±0.05 | 0.05±0.08 | 0±0 | 0±0 |
| MGBC113645 | 0.02±0.1 | 0±0 | 0.05±0.17 | 0±0 |
| CAKSEI01 | 0.02±0.04 | 0±0 | 0.04±0.06 | 0.01±0.01 |
| UMGS1994 | 0.02±0.05 | 0±0 | 0.04±0.09 | 0.01±0.01 |
| Fusicatenibacter | 0.02±0.05 | 0±0 | 0±0.01 | 0.05±0.07 |
| Wohlfahrtiimonas | 0.01±0.08 | 0±0 | 0.04±0.14 | 0±0 |
| Onthousia | 0.01±0.08 | 0±0 | 0.04±0.13 | 0±0 |
| UMGS1754 | 0.01±0.06 | 0±0 | 0.03±0.1 | 0±0 |
| Caccenecus | 0.01±0.06 | 0±0 | 0.03±0.09 | 0.01±0.02 |
| UBA1752 | 0.01±0.04 | 0±0 | 0.02±0.08 | 0±0.01 |
| CAG-272 | 0.01±0.05 | 0±0 | 0.02±0.08 | 0±0 |
| Pseudomonas | 0.01±0.01 | 0±0.01 | 0±0 | 0.01±0.01 |
| JABCPE02 | 0±0 | 0±0 | 0±0 | 0±0 |
| Streptococcus | 0±0 | 0±0 | 0±0 | 0±0 |
| Alysiella | 0±0 | 0±0 | 0±0 | 0±0 |
| Neisseria | 0±0 | 0±0 | 0±0 | 0±0 |
| HGM08974 | 0±0 | 0±0 | 0±0 | 0±0 |
| Pelistega | 0±0 | 0±0 | 0±0 | 0±0 |
| Moraxella | 0±0 | 0±0 | 0±0 | 0±0 |
| Actinobacillus | 0±0 | 0±0 | 0±0 | 0±0 |
| GN02-873 | 0±0 | 0±0 | 0±0 | 0±0 |
genus_arrange <- genus_summary %>%
group_by(genus) %>%
summarise(mean=sum(relabun)) %>%
filter(genus != "g__")%>%
arrange(-mean) %>%
select(genus) %>%
mutate(genus= sub("^g__", "", genus)) %>%
pull()
genus_summary_sort <- genus_summary %>%
group_by(genus) %>%
summarise(mean=mean(relabun, na.rm=T),sd=sd(relabun, na.rm=T)) %>%
arrange(-mean)
genus_summary %>%
mutate(genus=factor(genus, levels=rev(genus_summary_sort %>% pull(genus)))) %>%
filter(relabun > 0) %>%
ggplot(aes(x=relabun, y=genus, group=genus, color=phylum)) +
scale_color_manual(values=phylum_colors) +
geom_jitter(alpha=0.5) +
facet_grid(.~diet)+
theme_minimal() +
theme(axis.text.y = element_text(size=6))+
labs(y="Family", x="Relative abundance", color="Phylum")